After coverage of foundational concepts, remaining chapters cover optimality in optimal control problems, Lagrange multipliers, Pontryagin's minimum principle, different types of problems, numerical solution, optimal periodic control, and mathematical review.
What does LM stand for?
LM stands for Lagrange Multiplier
This definition appears frequently and is found in the following Acronym Finder categories:
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We have 60 other meanings of LM in our Acronym Attic
- Left Lower Zone (lung region)
- Lounge Lizard
- Leerplichtige Leerlingen Zonder Onderwijs (Dutch: Students Without School Education; educational study; Groningen, Netherlands)
- Labor Month
- Lactancia Materna (Spanish: Breastfeeding)
- LadderMonkey (gaming league)
- Ladies' Meeting
- Lady Macbeth
- Lady Madonna (Beatles song)
Samples in periodicals archive:
Lagrange Multiplier Adjunction: For each MPC, an additional unknown is adjoined to the master stiffness equations.
The Lagrange Multiplier (LM) test (Burridge 1980), which follows a chi-square distribution with one degree of freedom, can help detect the presence of spatial dependence in the form of an omitted spatially lagged dependent variable and/or spatial error dependence (Anselin 1988).
3]0 is the s-vector of Lagrange multipliers for the path constraints, and [v.
Examples of topics addressed include entropy solutions of nonlinear elliptic-parabolic-hyperbolic degenerate problems in one dimension, the comparison principle for a class of coupled systems of fully nonlinear parabolic equations under nonlocal boundary conditions, information complexity of evolutionary dynamics, the modified Lagrange multiplier rule and its application to the regularity of magnetic flux function in nuclear fusion, variational hyperbolic inequality in the domains unbounded in spatial variables, representation of exact solution of the compound Burgers-Korteweg-de Vries equation, and critical curves for a degenerate parabolic system with nonlinear boundary conditions.
The previous optimization problem is a convex quadratic program which can be solved by using the well-known Lagrange multiplier method.
Moreover, in the general case in which this steady state is not Pareto optimal, the quadratic approximation of household welfare depends on the steady-state values of the Lagrange multipliers of the original policymaking problem (Benigno and Woodford, 2005).